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Table 2 Included articles

From: Economic globalization, nutrition and health: a review of quantitative evidence

  Included Articles Methods Definition of trade liberalization Outcome variable Region Years Main findings Type of evidence
1 (de Soysa and de Soysa, 2017) Multivariate regression using country-level panel data KOF index of globalization. Analyse trade openness and FDI components separately Prevalence of obesity in young people aged 2–19 from GBD study 180 countries 1990–2013 Trade openness and economic globalization result in lower obesity rates among the younger groups of population BABCA
2 (Oberländer, Disdier, and Etilé, (2016) Multivariate regression using country-level panel data KOF index of globalization. Economic and social components analysed separately Prevalence of diabetes; BMI; markers of dietary quality (animal protein, free fat, sugar) 70 countries 1970–2011 Economic globalization negatively impacts health outcomes; socio-cultural globalization increases supplies of animal protein and sugar BAACA
3 (Costa-Font and Mas, (2016) Multivariate regression using country-level panel data KOF index of globaliztion; economic and social components analysed separately; CSGR index Prevalence of obesity 26 HIC 1989–2004 Globalization significantly increases obesity; economic component reduces obesity (effect non-significant when accounting for various controls and potential mechanisms); social component increases obesity BAACA
4 Goryakin et al., (2015) Multi-country multi-level panel data controlling for both individual and country-level covariates. KOF index of globalization and sub-components (economic, political, social) Overweight and obesity 56 countries 1991–2009 Globalization increases overweight, but the social and political components are the most relevant ABBAA
5 Miljkovic et al., (2015) Multivariate regression using country-level panel data FDI; trade openness; Global Socialization Index (GSI) Prevalence of obesity 76 countries 1986–2008 Trade openness increases obesity in the fixed effects specification, but not in the quantile regression. FDI and GSI increase obesity for least developed countries, where obesity rates are low BABCB
6 Sudharsanan,et al., (2015) Non-parametric correlation and multivariate first-difference regression estimates FDI prevalence of diabetes in 10-year age groups both HIC and LMIC 1990, 2000, 2008 Once ageing in population is taken into account, there is no evidence of FDI or other macroeconomic variables such as GDP, having an influence on prevalence of diabetes BABAC
7 Nandi et al., (2014) Meta-regression using multi-country cross-sectional individual level data. Mean tariff percentage averaged 1990–1999. FDI BMI; odds of being underweight, overweight and obese at the individual level for women in LMIC 40 LMIC 2002–2003 Tariff reduction is associated with lower odds of being underweight. FDI is associated with higher odds of being overweight among rural men only. Higher income is associated to higher odds of being overweight CAAAC
8 Neuman et al. (2014) Multi-level modelling using cross-sectional data FDI, mean tariff levels BMI; over and under-weight 38
1991, 2010 FDI is positively associated with BMI among poorest respondents in rural areas BAAAB
9 Vogli, R. de et al., (2014) Multivariate regression using country-level panel data. KOF index of globalization (economic component) BMI 127 countries 1980–2008 Globalization is positively associated to an increased BMI. Inequality also shows a positive association in high-income countries BABCA
10 Schram, Labonte, and Sanders (2013) Trend analysis and Structural Equation Modelling using multi-country cross-sectional data KOF index of economic globalization CVD, overweight, obesity 39 countries 2008 for SEM Economic globalization negatively impacts all health outcomes. CAACC
Context-relevant proxies of nutrition outcomes
11 Jenkins and Scanlan (2001) Multivariate regression analysis with country-level panel data. Foreign investment, dependence on primary exports Child undernutrition (weight-for-age), per capita energy and protein availability 88 less developed countries 1970–1990 There is a negative association between dependence on non-service exports and energy supply but this is non-significant after controlling for other economic variables. Neither FDI nor export dependence have an impact on child underweight BAACA
12 Dithmer and Abdulai (2017) Multivariate regression using country-level panel data. Trade openness energy consumption; diet diversity; diet quality 151 countries 1980–2007 Trade openness increases average dietary energy consumption, dietary diversity and indicators of dietary quality BAACA
13 Baker et al. (2016) Difference-in-difference/Natural experiment Ratification and enforcement of FTA with US per capita sales of soft drinks Peru 1999–2013 The study finds a diversification of soft drinks. Sales of carbonated drinks stagnate, but bottled water, sports and energy drinks increase AACCC
14 Schram A, Labonte R et al., (2015) Difference-in-difference/Natural experiment Adoption of trade agreement, FDI Consumption of carbonated beverages Vietnam and Philippines 1995–2012 The adoption of a trade agreement increases per-capita sales of beverages AACCA
15 Ogundari, (2015) Multivariate regression using country-level panel data. Trade openness Nutrient supply, calories, proteins, fat 43 countries 1975–2009 Trade openness seems to contribute to nutrient supply convergence in Sub-Saharan Africa BACCA
16 Zakaria (2014) Multivariate regression analysis using country-level panel data Trade openness Per capita availability of energy, fat 5 South Asian countries 1972–2013 Trade openness and tariff reductions are associated with increased energy availability per capita BACCA
17 Bezuneh and Yiheyis, (2014) Multivariate regression analysis using country-level panel data Implementation of liberalization policies (defined through dummy variables) Per capita dietary energy supply 37 developing countries 1980–2000 The removal of trade barriers is associated to short-term falls in nutrient availability per capita, with positive longer-term effects and insignificant “net” impacts BACCC
18 Stuckler et al. (2012) Multivariate regression analysis. FDI, trade agreement with US Sales per capita of sugar-sweetened beverages (SSB) 44 LMIC 1997–2010? Both FDI and trade agreements with US increase sales per capita of SSB. Economic growth in the absence of FDI does not increase sales of SSB BACCC
19 Djokoto (2012) Cointegration analysis, time series using country-level data FDI into agricultural sector Per capita dietary energy supply Ghana   FDI into the agricultural sector is detrimental for food security in Ghana BACCC
20 Mihalache and O’Keefe (2011) Cointegration analysis, time series using country-level data FDI into primary sector, manufacturing and service sector Per capita dietary energy supply 56 LMIC 1981–2001 FDI into the primary sector is detrimental for food security. FDI into manufacturing improves food security, FDI into services has ambiguous effects BACCA
21 Del Ninno and Dorosh (2003) Natural experiment. The authors compare three episodes of intense floods, their impact on crops, availability and price of rice, and calorie intake of affected households compared to those not affected Liberalization of private-sector rice imports from India, in the early 1990s Daily energy intake per capita Bangladesh 1977, 1988, 1998 In the absence of private sector imports, per capita consumption of the rural poor would have decreased by 44 to 109 Kcal/Day, (out of an average of 1636). Public interventions including price stabilization and transfers also play an important role AACCA
22 Wimberley and Bello (1992) Multivariate regression analysis using country-level panel data Primary export dependence; Transnational Company (TNC) investment Per capita energy, and protein availability, total and from vegetable sources 59 third world countries 1967–1985 There is evidence of a negative association between FDI and nutrition-related outcomes in developing countries, as well as a much smaller negative association for dependence on non-service exports BACCA
23 Wimberley (1991) Multivariate regression analysis using country-level panel data TNC investment Per capita energy and protein availability 60 Third World Countries 1970–1985 There is a strong negative association between FDI and per capita availability of energy and protein in developing countries BACCA
24 Gacitúa & Bello (1991) Multivariate regression analysis using country-level panel data Non-service exports as a proportion of GDP Per capita energy, protein availability total and from vegetable; Z-score standardized measure of calorie and protein consumption 15 Latin-American Countries 1967–1985 This study finds a negative association between dependence on non-service exports and per capita supply of energy and proteins in Latin America BACCC
Key literature reviews
1 Barlow et al., (2017) Systematic review Adoption of trade and investment agreements Health outcomes, risk factors   Trade and investment agreements can increase risk factors for NCD (beverage consumption) while also affecting protective factors (public health policies). However, certain agreements can increase access to patented medicines, with positive impacts on health  
2 Baker P, Kay A, Walls H. (2014) Semi-structured review Trade liberalization, trade and investment agreements, others prevalence of NCDs and main risk factors ASEAN+ 3, India Trade liberalization can promote NCD through two main pathways: increasing access to unhealthy products and constraining governments’ space to promote health  
3 Friel et al., (2013) Review of literature and pathway mapping Trade liberalization, trade and investment agreements, others NCDs, obesity Not restricted The authors identify several pathways through which trade liberalization can affect NCD  
4 McCorriston S et al. (2013) Systematic Review Various. Trade and related policies Food Security Developing Countries The authors find mixed evidence and a strong context-dependence of associations and impacts  
  1. Type of evidence. Design (A: natural experiment, B:longitudinal/time-series-cross-sectional (TSCS) or time series, C: cross-sectional); Statistical analysis (A: structural equation modelling, reduced-form regression, time-series analysis, other, B: simple one-on-one correlations, C: descriptive) Type of outcome variable (A: Uses several related outcome variables including prevalence or status of dietary-related disease as well as relevant proxies, B: Nutrition outcomes: Prevalence/status of diet-related disease (CVD, diabetes or others). Relevant biomarkers (obesity, underweight or overweight, BMI), C: Context-relevant proxies for nutrition outcomes: per capita consumption of key foods/nutrients); Data (A: Both individual and country-level outcome variables, B: Individual-level outcomes, C: Country-level outcome variables); Sensitivity analysis (A: Thorough: on outcome variables / regressors as well as on model specification and outliers, B: Some sensitivity analysis (eg. on regressors), C: No) See Additional file 2. *The category longitudinal/TSCS would include both studies that follow a sample of individuals over time, and those that include repeated observations at the country level, studying change over time with the country as unit of analysis